Column

Chart A: Boxplot

Let’s create a bax plot showing the distribution of people’s order hour for each aisle

data("instacart")
box = instacart|>
  group_by(aisle,order_hour_of_day)|>
  mutate(n_order=n())|>
  filter(n_order>1000)

plot_ly(box,x = ~aisle, y = ~order_hour_of_day,color=~aisle, type = "box",colors="viridis")

Column

Chart B: Barplot

Let’s make a bar plot to visualize the number of popular products in each aisles

day = instacart|>
  group_by(aisle)|>
  summarize(n_products=n())|>
  filter(n_products>10000)|>
  mutate(aisle=fct_reorder(aisle,n_products))

plot_ly(day, x=~aisle,y=~n_products,color=~aisle,type="bar",colors="viridis")

Chart C: Lineplot

summary = instacart |> 
  group_by(order_hour_of_day) |> 
  summarize(
    average_days_since_prior = mean(days_since_prior_order, na.rm = TRUE))

plot_ly(data = summary,
        x = ~order_hour_of_day,
        y = ~average_days_since_prior,
        type = "scatter",
        mode = "lines+markers") |> 
  layout(title = "Average Days Since Prior Order by Order Hour of the Day",
         xaxis = list(title = "Order Hour of Day"),
         yaxis = list(title = "Average Days Since Prior Order"))